Subodh Pushkar
LLMOps - Generative Retrieval
Tokyo, Japan
Summary
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Rockstar🎓
Top SchoolSubodh Pushkar is an MLOps and ML Infrastructure engineer based in Tokyo with 9 years of experience and a 6+ year focus on building scalable ML systems, observability, and deployment pipelines. At Mercari he designed MonitorX using Evidently AI for unified model monitoring, integrated Triton logging for online observability, and led Kubeflow upgrades that cut storage costs by $65K/year while enabling multi-tenancy. He has a strong track record of improving inference performance and reliability—migrating core services to GCP with autoscaling to boost throughput by 30%—and has productionized high-accuracy models with optimized Kubernetes training/serving pipelines. Trained in Math and Computer Science at IIT Delhi, he blends deep ML platform engineering with pragmatic cost and security improvements, often focusing on cross-team automation and lifecycle data management that aren’t obvious from model metrics alone.
9 years of coding experience
1 year of employment as a software developer
Indian Institute of Technology Delhi (IIT Delhi)
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (46)
jupyter9
google-kubernetes-engine9
notebook9
machine-learning9
kubeflow9
pipeline9
minikube9
kubeflow-pipelines8
github-token8
mlops8
tensorflow8
google-cloud-platform8
kubernetes8
requirements-management8
data-science8
Programming languages (8)
Github contributions (5)
subodh101/glucoma_segmentation
Aug 2018 - Oct 2018
Contributions:15 commits, 13 pushes, 1 branch in 2 months
subodh101/subodh101.github.io
Aug 2019 - Nov 2022
Website
Contributions:65 commits, 13 PRs, 71 pushes in 3 years 3 months
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